Mr. Mohamed saber | Renewable energy | Best Researcher Award

Mohamed saber | Renewable energy | Best Researcher Award

Mohamed saber, Zagazig University, Egypt

Mohammed Al-Desouky 🎓 is a Lecturer Assistant and Civil Hydraulic Engineer at Zagazig University, Egypt 🏛️. He holds a B.Sc. in Civil Engineering (2019) and is completing his M.Sc. in Water and Water Structures Engineering (2025) 💧. Passionate about hydraulic structures, CFD, and renewable energy ⚙️🔬, Mohammed co-founded the CIVIC construction company 🏗️. His research explores innovative energy solutions like pico hydropower using water wheels ⚡. A dedicated educator and engineer, he combines academic excellence with practical fieldwork, evident in his role in teaching, lab supervision, and structural design 📘💼.

Professional profile :

Orcid

Suitability for Best Researcher Award :

Mohammed Al-Desouky demonstrates a commendable blend of academic commitment, innovative research, and practical engineering application. His ongoing M.Sc. research in Water and Water Structures Engineering focuses on pioneering energy solutions such as pico hydropower with water wheels, an area that addresses both sustainability and energy accessibility—critical global challenges.

Education & Experience :

🎓 Education :

  • M.Sc. in Water and Water Structures Engineering, Zagazig University (2025) 💧

  • B.Sc. in Civil Engineering, Zagazig University (2019) 🏗️ — Excellent with Honor (88.65%)

💼 Experience :

  • Lecturer Assistant, Zagazig University (2019–Present) 👨‍🏫

  • Civil Hydraulic Engineer, Irrigation and Hydraulics Lab 🌊

  • General Contracting Engineer (2022–Present) 🧱

  • Structural Design Freelancer (2020–2021) 📐

  • CFD Engineer – Freelance 💻💨

  • Co-founder, CIVIC Construction Company 🏢

Professional Development :

Mohammed Al-Desouky has pursued dynamic professional development through hands-on internships and continuous upskilling 🚀. He completed an intensive 3-month internship with AECOM on Qatar’s Orbital Road Project, gaining cross-disciplinary training in utilities, structural works, and road construction 🛣️🏗️. Technically skilled in CFD simulation tools like ANSYS Fluent and FLOW-3D 💻🔍, he also brings expertise in structural software (SAP2000, ETABS, SAFE) for design and analysis 📊. His passion for practical learning is also evident in his leadership role at CIVIC, combining entrepreneurship with engineering innovation 🤝⚙️. Mohammed continuously aligns his growth with real-world engineering challenges and sustainability goals 🌍.

Research Focus :

Mohammed Al-Desouky’s research centers on sustainable hydropower and hydraulic systems 🔬⚡. His current work investigates energy harvesting from low-head water structures using waterwheels, aiming to optimize designs for pico-hydropower applications 🌊🌀. Combining experimental and numerical methods, including CFD simulations (ANSYS Fluent, FLOW-3D) 💻📈, his research contributes to renewable energy solutions and small-scale power generation in developing areas 🌍⚙️. He also explores techno-economic viability, integrating civil hydraulics, fluid mechanics, and structural analysis to develop practical, cost-effective innovations 💡💰. His publication in Renewable Energy reflects a strong commitment to energy-efficient and environmentally friendly infrastructure development 🌿🔋.

Awards and Honors :

  • 🎓 Graduated with Excellent with Honor in B.Sc. Civil Engineering (2019)

  • 🏅 Publication in Renewable Energy Journal (2024)

  • 🏗️ Selected for AECOM Internship, Orbital Road Project – Qatar

  • 🧠 Co-founded CIVIC Construction Company

Publication Top Notes : 

Title: Techno-economic Assessment of the Dethridge Waterwheel under Sluice Gates in a Novel Design for Pico Hydropower Generation

Journal: Renewable Energy
Publication Date: August 2024
DOI: 10.1016/j.renene.2024.121206
ISSN: 0960-1481

Citation (APA Style):
Saber, M., Abdelall, G., Ezzeldin, R., AbdelGawad, A. F., & Ragab, R. (2024). Techno-economic assessment of the Dethridge waterwheel under sluice gates in a novel design for pico hydropower generation. Renewable Energy, 213, 121206. https://doi.org/10.1016/j.renene.2024.121206

Conclusion :

Mohammed Al-Desouky exemplifies the spirit of the Best Researcher Award through his innovative, applied research and multi-dimensional contributions to civil engineering, education, and sustainable energy. His early achievements and commitment to practical impact position him as a promising researcher with significant potential to influence the future of water infrastructure and renewable energy systems.

Prof. Tian Tian | Renewable Energy | Best Researcher Award

Prof. Tian Tian | Renewable Energy | Best Researcher Award

Prof. Tian Tian, Yangzhou University, China

Dr. Teng Huang is a distinguished researcher at Guangzhou University, China, specializing in Blockchain, Smart Contracts, and AI-driven Medical Image Segmentation. His work integrates Comprehensive Transformer Integration Networks (CTIN) to enhance medical diagnostics. With numerous high-impact publications in IEEE and other top journals, Dr. Teng Huang has contributed significantly to breast lesion detection, brain tumor segmentation, and privacy-preserving AI. His expertise extends to remote sensing, recommendation systems, and adversarial learning. Dr. Teng Huang’s innovative research bridges healthcare, AI, and blockchain, establishing him as a leader in computational intelligence and medical AI applications.

🌍 Professional Profile:

Orcid

🏆 Suitability for Best Researcher Award 

Dr. Teng Huang’s groundbreaking contributions in medical imaging, blockchain security, and AI-driven diagnostics make him a strong candidate for the Best Researcher Award. His work on transformer-based segmentation models, privacy-preserving AI, and federated learning has significantly advanced both healthcare and secure computing. With publications in prestigious journals like IEEE Transactions on Medical Imaging and IEEE Journal of Biomedical and Health Informatics, Dr. Teng Huang has demonstrated exceptional research impact. His multi-disciplinary expertise, innovative problem-solving, and commitment to scientific excellence set him apart as a leader in AI-driven healthcare solutions and blockchain applications.

📚 Education

Dr. Teng Huang holds a Ph.D. in Computer Science, specializing in Artificial Intelligence, Blockchain, and Medical Image Processing. His academic journey includes extensive research on deep learning architectures for healthcare and secure computing. His doctoral studies focused on optimizing transformer-based AI models for medical applications, particularly in breast cancer detection and brain tumor segmentation. He has also worked on privacy-preserving federated learning for secure data sharing in healthcare. Dr. Teng Huang’s educational background has equipped him with expertise in machine learning, optimization, and blockchain security, paving the way for his innovative contributions to AI-driven healthcare solutions.

👨‍🏫 Experience 

Dr. Teng Huang is a faculty member and researcher at Guangzhou University, China, where he leads projects on blockchain security, AI-driven diagnostics, and remote sensing applications. He has collaborated with international experts in biomedical image processing, adversarial AI, and recommendation systems. His work in privacy-preserving federated learning has been instrumental in enhancing data security in medical AI applications. With experience in designing intelligent models for 3D medical segmentation, ultrasound imaging, and smart contracts, Dr. Teng Huang continues to push the boundaries of AI research and secure computing, making significant contributions to both academia and industry.

🏅 Awards & Honors 

Dr. Teng Huang has received multiple Best Paper Awards at IEEE international conferences for his pioneering work in AI-driven medical imaging and blockchain security. He has been recognized as a Top Researcher in AI for Healthcare by leading institutions. His contributions to transformer-based medical diagnostics and federated learning security have earned him prestigious grants and funding. He is also a recipient of the Outstanding Young Researcher Award for his work in privacy-preserving AI and adversarial learning techniques. His innovative AI-driven solutions for medical imaging and remote sensing have positioned him as a global leader in computational healthcare research.

🔬 Research Focus 

Dr. Teng Huang specializes in Blockchain, Smart Contracts, Medical Image Processing, and AI-driven Healthcare Innovations. His research involves Comprehensive Transformer Integration Networks (CTIN) for advanced medical image segmentation in breast lesion and brain tumor detection. He is also working on privacy-preserving federated learning for secure medical data exchange. His expertise extends to adversarial learning, recommender systems, and remote sensing AI applications. By integrating deep learning, blockchain security, and smart contracts, Dr. Teng Huang is revolutionizing secure AI-driven diagnostics. His work significantly impacts healthcare, cybersecurity, and AI-based automation for next-generation medical solutions.

📊 Publication Top Notes:

  1. Emission and Absorption Spectroscopic Techniques for Characterizing Perovskite Solar Cells

    • Year: 2024

  2. Advancing Perspectives on Large-Area Perovskite Luminescent Films

    • Year: 2024

  3. Reducing Lead Toxicity of Perovskite Solar Cells with a Built-in Supramolecular Complex

    • Year: 2023

  1. Unlocking Multi-Photon Excited Luminescence in Pyrazolate Trinuclear Gold Clusters for Dynamic Cell Imaging

    • Year: 2024

  2. Durable Organic Nonlinear Optical Membranes for Thermotolerant Lightings and In Vivo Bioimaging

    • Year: 2023